The Research Scientist role today
This guide draws on 309 Research Scientist postings from 186 companies, published from March to September 2026.
Research Scientist is a core AI role: in 100% of postings, building or applying AI is the job itself.
Machine Learning appears in 24% of Research Scientist postings, and Deep Learning in 9%.
Automation exposure averages 27 out of 100 across these postings, which is low: AI mostly supports this work rather than taking it over.
Entry-level positions make up 46% of postings, senior 27%. The most common way of working is on-site, in 43% of postings.
Common skill gaps
The AI skills our analysis of Research Scientist job descriptions most often flags as a gap, with the share of postings where each one comes up.
- AI Ethics in Research13%
- MLOps10%
- AI Ethics10%
- Machine Learning Fundamentals8%
- AI ML Fundamentals7%
- Deep Learning Frameworks6%
Essential Research Scientist skills
The skills employers ask for in Research Scientist job descriptions, from the most requested down.
Core skills
- Python
- Machine Learning
- Data Analysis
Also valued
- Research Methodology
- Deep Learning
- AI Tools Literacy
- PyTorch
- Statistical Modeling
- Reinforcement Learning
- AI Assisted Data Analysis
AI skills to learn next
The AI skills employers most often want to add to this role, beyond the ones above.
- Python Programming
- Python for Data Science
- Machine Learning Basics
How the Research Scientist role is evolving
The directions employers are taking this role as they adopt AI, with the skills and responsibilities each one adds.
Most common direction
Toward AI research
Typical focus
AI-augmented discovery, AI reasoning and AI-driven materials discovery
Skills to add
- Data Visualization
New responsibilities
- Apply machine learning models to predict material properties and guide experimental design
- Collaborate with data scientists to build and maintain materials databases
- Build and maintain a knowledge graph linking proteins, targets, and evidence to support automated discrepancy detection
- Collaborate with data scientists to integrate AI into research workflows
Other directions
Toward data & machine learning
Typical focus
Data science, AI data & evaluation and AI data quality
Skills to add
- Cloud Computing
New responsibilities
- Apply machine learning models to predict purification outcomes and optimize process parameters
- Develop and maintain data pipelines for high-throughput experimentation data
- Mentor team members on data science best practices
- Analyze data distributions to identify gaps in STEM problem coverage
Toward AI transformation
Typical focus
Digital bioprocessing, Digital transformation and Digital lab transformation
Skills to add
- Change Management
- AI Project Management
- AI Strategy
- AI Tool Evaluation
- Digital Transformation
- Change Management for AI Adoption
New responsibilities
- Train and mentor staff on AI tools and data-driven decision-making
- Advise clients on integrating AI into their drug discovery pipelines
- Advise executive leadership on emerging AI trends and their strategic implications
- Advise leadership on AI investment priorities to maximize scientific and operational impact
Toward AI engineering
Typical focus
AI systems and Robot learning systems
Skills to add
- Model Optimization
- Distributed Training
- Model Deployment
- Software Engineering
New responsibilities
- Architect and optimize real-time inference pipelines for ASR, MT, and TTS models, ensuring ultra-low latency and high throughput
- Architect and optimize the end-to-end training and deployment pipeline for robot control policies
- Automate data collection and analysis pipelines for research experiments
- Benchmark and improve inference efficiency for production-grade drug discovery models
Research Scientist FAQ
Will AI replace Research Scientist jobs?
Automation exposure averages 27 out of 100 across these postings, which is low: AI mostly supports this work rather than taking it over. Employers are mostly reshaping the role toward AI research, adding skills such as Machine Learning and Reinforcement Learning.
What skills do Research Scientist roles require?
The skills employers ask for most are Python, Machine Learning, Data Analysis, Research Methodology and Deep Learning.
Which AI skills should Research Scientist candidates learn next?
Machine Learning, Data Analysis and Python are the AI skills employers most often want to add. The most common skill gaps are AI Ethics in Research and MLOps.
How is the Research Scientist role changing?
The most common direction is AI research. Other directions include data & machine learning, AI transformation and AI engineering.
Find your next Research Scientist role
Browse open AI roles, updated daily.
This guide is built from public job descriptions for Research Scientist roles classified as Core AI or AI-enabled. Skills, automation exposure and career directions are extracted from each job description and compared across the market. Postings are deduplicated, so a job listed on several boards or by several agencies counts once. How we collect and deduplicate postings.